Gartner Cloud DBMS Report Names MarkLogic a Visionary

London – March 15, 2019 – MarkLogic Corporation, the next generation data platform provider for simplifying complex data integration, is today celebrating winning the Data, Information management or Analytics Solution of the Year category at the 2019 European Software IT & Excellence Awards.

Run by IT Europa, a provider of strategic business intelligence, news and analysis on the European IT marketplace, the European IT & Software Excellence Awards is Europe’s most prestigious IT Channel Awards programme. Now in its 11th year, the Awards recognise and reward excellence in European software development and IT and Telecoms solutions provision.

An independent panel of six judges selected MarkLogic as the outstanding entry in the Data, Information management or Analytics Solution of the Year category for its work with one of Europe’s leading banks.

Using MarkLogic’s NoSQL database solution, the bank has been able to take all of its complex trading data, in its original form, and store it in one place. This has given the company a 360-degree view of all trading data, as opposed to previously siloing the data in many different solutions that were unable to interact.

MarkLogic® was also praised for its outstanding security credentials as the only NoSQL database to be awarded Common Criteria Certification. The Common Criteria for Information Technology Security Evaluation (or “Common Criteria”) is an international standard for security by which vendors demonstrate their commitment and ability to provide security to their customers.

For the full list of all winners in the 2019 European Software IT & Excellence Awards visit https://www.iteawards.com


 

About MarkLogic

MarkLogic helps customers create value from complex data faster. Our platform ingests data from any source, creating and refining metadata to support powerful models. Customers use these models for deep search and query, building enterprise applications and bringing unique insights to analytics and machine learning.

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